R: Cross-correlation between two frequency spectra

corspec {seewave}

R Documentation

Cross-correlation between two frequency spectra

Description

This function tests the similarity between two frequency spectra by returning their maximal correlation and the frequency shift related to it.

Usage

corspec(spec1, spec2, f = NULL, mel = FALSE, plot = TRUE, plotval = TRUE,
method = "spearman", col = "black", colval = "red",
cexval = 1, fontval = 1, xlab = NULL,
ylab = "Coefficient of correlation (r)", type="l",...)

Arguments

`spec1`	a first data set resulting of a spectral analysis obtained with `spec` or `meanspec` (not in dB). This can be either a two-column matrix (col1 = frequency, col2 = amplitude) or a vector (amplitude).
`spec2`	a first data set resulting of a spectral analysis obtained with `spec` or `meanspec` (not in dB). This can be either a two-column matrix (col1 = frequency, col2 = amplitude) or a vector (amplitude).
`f`	sampling frequency of waves used to obtain `spec1` and `spec2` (in Hz). Not necessary if `spec1` and/or `spec2` is a two columns matrix obtained with `spec` or `meanspec`.
`mel`	a logical, if `TRUE` the (htk-)mel scale is used.
`plot`	logical, if `TRUE` plots r values against frequency shift (by default `TRUE`).
`plotval`	logical, if `TRUE` adds to the plot maximum r value and frequency offset (by default `TRUE`).
`method`	a character string indicating which correlation coefficient is to be computed ("pearson", "spearman", or "kendall") (see `cor`).
`col`	colour of r values.
`colval`	colour of r max and frequency offset values.
`cexval`	character size of r max and frequency offset values.
`fontval`	font of r max and frequency offset values.
`xlab`	title of the frequency axis.
`ylab`	title of the r axis.
`type`	if `plot` is `TRUE`, type of plot that should be drawn. See `plot` for details (by default "l" for lines).
`...`	other `plot` graphical parameters.

Details

It is important not to have data in dB.
Successive correlations between spec1 and spec2 are computed when regularly shifting spec2 towards lower or higher frequencies.
The maximal correlation is obtained at a particular shift (frequency offset). This shift may be positive or negative.
The corresponding p value, obtained with cor.test, is plotted.
Inverting spec1 and spec2 may give slight different results, see examples.

Value

If plot is FALSE, corspec returns a list containing four components:

`r`	a two-column matrix, the first colum corresponding to the frequency shift (frequency x-axis) and the second column corresponding to the successive r correlation values between `spec1` and `spec2` (correlation y-axis).
`rmax`	the maximum correlation value between `spec1` and `spec2`.
`p`	the p value corresponding to `rmax`.
`f`	the frequency offset corresponding to `rmax`.

Author(s)

Jerome Sueur, improved by Laurent Lellouch

References

Hopp, S. L., Owren, M. J. and Evans, C. S. (Eds) 1998. Animal acoustic communication. Springer, Berlin, Heidelberg.

Examples

## Not run: data(tico)
## compare the two first notes spectra
a<-spec(tico,f=22050,wl=512,at=0.2,plot=FALSE)
c<-spec(tico,f=22050,wl=512,at=1.1,plot=FALSE)
op<-par(mfrow=c(2,1), mar=c(4.5,4,3,1))
spec(tico,f=22050,at=0.2,col="blue")
par(new=TRUE)
spec(tico,f=22050,at=1.1,col="green")
legend(x=8,y=0.5,c("Note A", "Note C"),lty=1,col=c("blue","green"),bty="o")
par(mar=c(5,4,2,1))
corspec(a,c, ylim=c(-0.25,0.8),xaxs="i",yaxs="i",las=1)
par(op)
## different correlation methods give different results...
op<-par(mfrow=c(3,1))
corspec(a,c,xaxs="i",las=1, ylim=c(-0.25,0.8))
title("spearmann correlation (by default)")
corspec(a,c,xaxs="i",las=1,ylim=c(0,1),method="pearson")
title("pearson correlation")
corspec(a,c,xaxs="i",las=1,ylim=c(-0.23,0.5),method="kendall")
title("kendall correlation")
par(op)
## inverting x and y does not give exactly similar results
op<-par(mfrow=c(2,1),mar=c(2,4,3,1))
corspec(a,c)
corspec(c,a)
par(op)
## mel scale
require(tuneR)
data(orni)
orni.mel <- melfcc(orni, nbands = 256, dcttype = "t3", fbtype = "htkmel", spec_out=TRUE)
orni.mel.mean <- apply(orni.mel$aspectrum, MARGIN=2, FUN=mean)
tico.mel <- melfcc(tico, nbands = 256, dcttype = "t3", fbtype = "htkmel", spec_out=TRUE)
tico.mel.mean <- apply(tico.mel$aspectrum, MARGIN=2, FUN=mean)
corspec(orni.mel.mean, tico.mel.mean, f=22050, mel=TRUE, plot=TRUE)

## End(Not run)

[Package seewave version 2.1.6 Index]